dinal Study of Adolescent Health, we examine pre-disease pathways in the relationship ... ciated with loneliness in adolescence and health in early adulthood.
Adolescent Loneliness and Health in Early Adulthood*
Bridget J. Goosby and Anna Bellatorre, University of Nebraska–Lincoln Katrina M. Walsemann, University of South Carolina Jacob E. Cheadle, University of Nebraska–Lincoln
The health consequence of loneliness in the early life course is an understudied topic in the sociological literature. Using data from Waves 1–3 of the National Longitudinal Study of Adolescent Health, we examine pre-disease pathways in the relationship between adolescent loneliness and early adult health. Our results indicate that loneliness during adolescence is associated with diagnosed depression, poorer adult self-rated health, and metabolic risk factors related to cardiovascular disease. High depressive symptoms and parent support are important pathways through which the health consequences of loneliness are exacerbated or offset. There is also evidence that lonely youth remain at higher risk for experiencing adult depression and poor self-rated health even in the presence of equivalent levels of parental support relative to non-lonely adolescents. Furthermore, lonely adolescent females are more vulnerable to reporting poor adult self-rated health and being overweight or obese in adulthood. In sum, our study demonstrates the importance of adolescent loneliness for elevating the risk of poor health outcomes in adulthood.
Introduction The desire to belong and feel socially connected is a fundamental aspect of human development and well-being. Although there is an extensive sociological literature examining the health implications of social support and social integration along with a growing literature assessing the harmful impact of loneliness (i.e., perceived social isolation) among the elderly (Savikko et al. 2005; Warner and Kelley-Moore 2012), there is a dearth of information regarding the potential health consequences of loneliness relative to other indicators of social integration at earlier life course stages. The omission of early life course loneliness in the sociological literature is somewhat curious because loneliness is an eminently social–psychological construct, reflecting how people experience the communal aspects of their social worlds. Indeed, we know little about the extent to which early life course loneliness influences health during the transition to adulthood or the pathways through which loneliness impacts early adult health. Loneliness may serve as an important, overlooked predisease pathway for a range of health outcomes in adulthood.
Sociological Inquiry, Vol. 83, No. 4, November 2013, 505–536 © 2013 Alpha Kappa Delta DOI: 10.1111/soin.12018
506
BRIDGET J. GOOSBY ET AL.
Adolescence is a particularly salient time for understanding the health consequences of loneliness because youth are experiencing various developmental transitions, from biological (i.e., pubertal onset) to social (e.g., transitioning from primary to secondary school). During this developmental stage, youth are also transitioning from their parents to their friends as primary socializing agents (Crosnoe 2000). Such a myriad of transitions can lead to both friendship instability and emotional distress, which could lead to a cascade of health risks over time. Social ties are salient for life course health (Umberson and Montez 2010). For adolescents specifically, both attachment to school and parental support may be key protective factors for mental and physical health during a developmental period when distress is high (Giordano 2003; Resnick et al. 1997). Using data from Waves 1–3 of the National Longitudinal Study of Adolescent Health (Add Health), we examine the social and psychological pathways through which loneliness influences early adult depression, self-rated health, and metabolic conditions associated with cardiovascular disease (CVD). To this end, our study expands the existing literature by applying a life course perspective to identify the psychological and social risk and protective pathways associated with loneliness in adolescence and health in early adulthood. Background Emile Durkheim presented foundational sociological research demonstrating the importance of social relationships and health in his 19th-century study of social integration and suicide (1951). Durkheim’s study underscores the importance of being socially connected and having high quality social connections for individual and societal health. Durkheim’s analysis of the relationship between suicide risk and social context demonstrate that disruptions in social connections (an example being economic upheaval) can lead to elevated levels of social alienation in individuals, affecting their mood and straining interactions with others, thereby leading to elevated risk of suicide at the societal level (Durkheim 1951). Durkheim’s analyses are undoubtedly generalizable to other health risks and are also importantly linked to the subsequent social science research examining role of social connectedness for health outcomes (Berkman et al. 2000; Thoits 2011). Social isolation, social integration, and loneliness have been studied with varying levels of interest across disciplines. Cornwell and Waite (2009) note that a challenge in previous research examining social isolation and health is the disciplinary disjuncture in how social isolation is studied and defined. Specifically, research in sociological literature focuses primarily on levels of social integration, defined as the “existence and quantity of social relationships” (House, Umberson, and Landis 1988; p. 293), while psychological literature
LONELINESS AND HEALTH
507
focuses primarily on perceived social isolation or the extent to which people consider themselves lonely (Cornwell and Waite 2009). The former is related both to social network structure (i.e., structural properties that characterize a set of relationships; House, Umberson, and Landis 1988) and the provision of social support (Gorman and Sivaganesan 2007), while the latter is not always synonymous with having smaller social networks or less objective social support (see Heinrich and Gullone 2006 for review). In this study, we focus specifically on the concept of loneliness (i.e., perceived social isolation) while accounting for objective measures of social integration as well as perceived support. Loneliness is a painful emotional state that occurs when there is “a discrepancy between…the desired and achieved patterns of social interaction” (Peplau and Perlman 1982, p. 5). Those who perceive themselves as lonely may not necessarily lack social relationships, but instead may consider their relationships as inadequate or poor in quality (Hawkley et al. 2010). Although loneliness is associated with objective social relationship characteristics such as the number of friends one has, there is not always agreement between subjective appraisals and objective measures. Several studies have demonstrated that the total number of friends people have does not adequately predict loneliness in children or adults (Fischer and Phillips 1982; Parker and Seal 1996). Moreover, it is important to note the distinction between social support and loneliness since lonely and non-lonely individuals are just as likely to interact with other people; however, for the lonely, their interactions are of lower quality and “provide them with less support and comfort” (Cacioppo, Hawkley, and Berntson 2003; p. 73). Furthermore, the perceived availability of social support and subjective ratings of relationship quality are each associated with loneliness and health (Hawkley et al. 2008). Loneliness from a Life Course Perspective The life course perspective is an effective framework to apply when investigating specific mechanisms through which stress-related health outcomes are manifested and operate over the early life course (Turner and Schieman 2008). Our study emphasizes particular tenets of the life course perspective to examine potential predisease pathways through which adolescent loneliness may influence health in early adulthood, including the study of human biological and developmental processes over time (e.g., transitioning from parent to peer socialization), the timing of and exposure to stressful life events (e.g., loneliness), and most essential, the degree to which individual lives are linked (Elder, Johnson, and Crosnoe 2004). Loneliness is most prevalent during adolescence with more than 70 percent of adolescents experiencing recurring loneliness at age 18, a rate that declines
508
BRIDGET J. GOOSBY ET AL.
to 60 percent by ages 35–40, and 39 percent for older adults (Heinrich and Gullone 2006; Parlee 1979; Savikko et al. 2005). Extant research using clinical and non-representative U.S. samples suggests that loneliness is directly associated with poorer mental and physical health during adolescence and early adulthood. For example, lonely adolescents report higher rates of depression and anxiety (Koenig and Abrams 1999), social withdrawal (Crick and Ladd 1993), suicide ideation and attempts (see Heinrich and Gullone 2006), psychosomatic complaints (i.e., headaches, nausea, etc.; Ponzetti 1990), and poorer overall general health (Mahon, Yarcheski, and Yarcheski 1993). The occurrence of loneliness is especially salient for adolescents as their desire to feel socially accepted and to belong becomes particularly intense during this developmental period (Brennan 1982). Loneliness is itself an important stressor and a salient aspect of the life course tenet of linked lives because how youth perceive the quality of their relationships, that is, how their lives are linked to others, can have far-reaching consequences for their mental and physical well-being. In addition to understanding the degree to which the perception of linked social lives directly influence health, understanding how the deleterious health consequences of loneliness are offset or moderated by social relationships is essential for identifying social mechanisms that influence individual and population-level health over time (House, Umberson, and Landis 1988). During adolescence, both parents and peers can provide supportive environments that offset stressors such as loneliness (Giordano 2003) and may also attenuate the relationship between loneliness and health. Parental warmth, both maternal and paternal, is associated with lower levels of loneliness in their offspring (Mahon et al. 2006). Parental support is also associated with adolescent health; adolescents’ perception of parental support (or lack thereof) is a significant predictor of adolescent general health complaints (Wickrama, Lorenz, and Conger 1997) and depressive symptoms (Cornwell 2003). School attachment, or the degree to which youth feel connected or close to people at their school, is also particularly protective. Youth who are well liked and feel supported by their friends are less likely to report feeling lonely, whereas lonely adolescents feel less integrated and attached to their school (Chipuer 2001; Kingery and Erdley 2007). Adolescents who do not feel like they are part of their school report poorer self-rated health and elevated depressive symptoms in early adulthood (Goosby and Walsemann 2012; Walsemann, Bell, and Goosby 2011), thus demonstrating the importance of social connections for subsequent health. Furthermore, the links between parent support and adolescent school attachment with loneliness and health suggest that these may be understudied mechanisms through which loneliness impacts health. Even in the presence of social support, however, lonely youth may be less able to adequately cope with stress (Larose and Bernier 2001). Specifically,
LONELINESS AND HEALTH
509
individuals who feel socially isolated may have more ambivalent, less secure attachment styles (Cacioppo et al. 2000) and elevated depressive symptoms (Cacioppo, Hawkley, and Thisted 2010), which can result in difficulty maintaining and mobilizing support during stressful circumstances. In a study of adolescents transitioning into college, Larose and Bernier reported that youth with less healthy attachment styles reported higher levels of loneliness and greater difficulty seeking out support from their peers and teachers (2001). Consequently, the inability to mobilize support may not only exacerbate the cycle of loneliness, it may also intensify health risks associated with a lack of social support and isolation. Lonely adolescents may therefore be at greater risk for deleterious health outcomes compared to adolescents who are not lonely, because lonely youth with ambivalent attachment styles can reduce the protective characteristics of social support that they may already be receiving. Gender Differences. In examining the potential consequences of loneliness for subsequent adult mental and physical health outcomes, there is a dearth of literature examining whether the consequences of adolescent loneliness for adult health are moderated by gender. Salient developmental gender differences emerge during adolescence. Specifically, girls begin to experience a 2:1 higher rate of depression than boys, a difference that persists into adulthood (Nolen-Hoeksema 2001). Research assessing gender differences in adulthood loneliness indicates that women are more likely to report higher rates of loneliness and depression relative to men (Borys and Perlman 1985), yet this pattern is not consistently found among adolescents. Indeed, boys generally report similar or higher rates of loneliness as girls (cf., Koenig and Abrams 1999 for a comprehensive literature review). According to Koenig and Abrams (1999), boys’ higher rate of loneliness is associated with their increased time spent alone as compared to adolescent girls who transition from spending time with their parents, to spending more time with their peers. An important limitation of this body of work, however, is that most of the findings are based on non-representative samples that only assessed gender differences in the rates of loneliness and not in their links to subsequent health. Although there may not be differences in rates of loneliness in adolescence, there may be differences in the health risk of loneliness for boys relative to girls, yet to be uncovered. Thus, we explore whether the impact of loneliness and health in adulthood varies by gender. Health Consequences of Loneliness Prior studies show that loneliness is associated with greater risk of physical health conditions such as obesity, vascular resistance, diminished immunity, alcoholism, and mortality in adults (see Cacioppo, Fowler, and Christakis
510
BRIDGET J. GOOSBY ET AL.
2009; Heinrich and Gullone 2006). There are several studies reporting that childhood loneliness is also linked to high blood pressure, high cholesterol, obesity, and major depressive disorder in adulthood (Cacioppo, Hawkley, and Thisted 2010; Caspi et al. 2006; Danese et al. 2009). Depression is also tied to an array of physical illnesses associated with cardiovascular disease including metabolic conditions (Joynt, Whellan, and O’Connor 2003; Kinder et al. 2004) and as such could be a risky pathway through which loneliness impacts health. The above-mentioned studies, however, do not account for the role of depressive symptoms during adolescence as a conduit connecting loneliness to later health—an important omission that we address in this study. Our study investigates the early life course loneliness pathways to early adulthood health by assessing the social processes that could offset or exacerbate the harmful influence of adolescent loneliness for subsequent health, while accounting for important gender differences in patterns of health outcomes related to loneliness and health. Building on the existing literature, we examine the degree to which loneliness in adolescence is associated with stress-related metabolic health conditions in early adulthood, including hypertension, high cholesterol, and obesity, as well as its effects on diagnosed depression and self-rated health, addressing the following hypotheses: H1—Loneliness is associated with poor mental and physical health; H2 and H3—Parent support (H2) and school attachment (H3) attenuate the adolescent loneliness and adult mental and physical health relationship; H4—Lonely youth who report high levels of parent support (H4a) and/or high levels of school attachment (H4b) will report poorer health outcomes than their non-lonely counterparts; H5—Depressive symptoms mediate the adolescent loneliness and adult health relationship. Finally, we examine whether lonely girls have a higher risk for poor adult health outcomes relative to boys.
Methods Data This study utilizes data from the National Longitudinal Study of Adolescent Health (Add Health), which is a nationally representative sample of U.S. adolescents from 132 middle and high schools. The sample design for this study was a complex area probability sample of students, clustered at the school level, and stratified to take into account school type (public, private, or parochial), school size, region of the country, and the level of urbanization. High schools were eligible if they had a feeder school also eligible for the study in the catchment area of the high school capable of enrolling five or more students into the focal high school. Wave 1 survey data collection was conducted in school and at home, whereas later waves were implemented in-home only. The Wave 1 in-school questionnaire was administered to students in 1994/5 prior to the Wave 1 in-home survey in 1995, and subsequent in-home
LONELINESS AND HEALTH
511
surveys were administered in 1996, 2001/2, and 2007/8 (Chantala and Tabor 1999). During the first wave of data collection, parents were also interviewed. In addition, data were collected from focal adolescents about dating and friendship patterns, health, substance use, and so on. Our sample utilizes data from Waves 1 (1994/1995), 2 (1996), and 3 (2001/2) and includes respondents with available information in Wave 3 on self-rated health and self-reported clinically diagnosed depression, hypercholesterolemia (high cholesterol), hypertension (high blood pressure), and body mass index (BMI). Multiple imputation by chained equations in Stata 12 (the ice command; Royston 2004) was employed to handle missing data on the covariates included in the analysis and to maintain the pattern of relationships among them (Little and Rubin 2002). The sample only includes cases that were not missing on the dependent variables. We replicated analyses across 10 imputation data sets and combined the results to produce final estimates using Rubin’s rules (see Royston, Carlin, and White 2009; Schafer 1999). The final sample sizes based on the dependent variables for the analyses were 10,576 for selfrated health, 10,564 for depression, 8,595 for overweight/obese, 10,560 for high cholesterol, and 10,567 for high blood pressure. Measures Dependent Variables. The focal analysis variables are self-rated health, diagnosed depression, and cardiovascular disease (CVD)-related metabolic conditions—overweight or obesity, diagnosed high cholesterol, and high blood pressure measured at Wave 3 when the youth were 18 to 27 years old. Respondents were asked “In general, how is your health? Would you say excellent, very good, good, fair, or poor?” Self-rated health was categorized as poor or fair health versus good to excellent health. Diagnosed hypertension, high cholesterol, and depression were self-reported. Self-reported diagnosed depression is included as both an outcome and a key covariate in the models assessing physical health conditions. Respondents who indicated a prior diagnosis of a condition were coded as “1” for that condition and “0” otherwise. Overweight/obese status was measured using adult BMI and was calculated using the respondents’ measured height and weight at Wave 3 as [weight (kg)/(height in meters)2]. Respondents were categorized as overweight or obese if their value exceeded 25. Loneliness and Risk and Protective Mechanisms. Loneliness at Wave 1 was measured using the following questions with responses on a 4-point scale (ranging from 0 = never or rarely to 4 = most of the time or all of the time): how often in the past seven days: (1) did you feel lonely, (2) did you feel that people disliked you, and (3) were people unfriendly to you. Respondents were also asked how much they agreed (on a scale from 1 to 5, where 1 = strongly
512
BRIDGET J. GOOSBY ET AL.
agree and 5 = strongly disagree) that they felt (1) loved and wanted and (2) socially accepted. Results from factor analysis on these five items were used to create factor scores. These scores predict the location of an individual on the latent loneliness factor; higher factor values represent higher levels of loneliness (Cronbach’s alpha W1 = .70). It is important to note that because the UCLA loneliness scale (Russell, Peplau, and Cutrona 1980), a validated measure of loneliness, was not available in Add Health, we created a scale that utilized several items from the CES-D scale and other scales that reflect dimensions of loneliness. Depressive symptoms in Wave 2 were measured using the 19 items from the CES-D scale. The Center for Epidemiological Studies Depression (CES-D) scale is a validated scale for measuring recent depressive symptoms experienced in the preceding week (Radloff 1977). The measure is used here to assess whether respondents experience high levels of depressive symptoms during Wave 2. The scale was summed and dichotomized; respondents with a score of 16 or higher were coded “1” for high depressive symptoms. All else were coded “0” (Yen et al. 2006). Parent support was measured using up to eight items reporting the quality of respondents’ relationship with their parents (four items for youth in singleparent families). Respondents were asked how much they agreed (on a scale from 1 to 5, where 1 = strongly disagree and 5 = strongly agree) that (1) most of the time, your mother is warm and loving to you; (2) you are satisfied with the way your mother and you communicate with each other; (3) overall, you are satisfied with your relationship with your mother; (4) most of the time, your father is warm and loving to you; (5) you are satisfied with the way your father and you communicate with each other; and (6) overall, you are satisfied with your relationship with your father. The parent support scale was averaged across mother and father scores and the average of standardized factor scores was calculated across Waves 1 and 2 (W1 alpha = .85, W2 = .85; r = .57), with higher scores denoting greater parental support. School attachment was measured with four items using a 5-point scale where students were asked how strongly they agreed (ranging from 1 = strongly disagree to 5 = strongly agree) with the following statements: (1) teachers at your school treat students fairly; (2) you feel you are part of your school; (3) you feel close to people at your school; and (4) you are happy to be at your school. School attachment was operationalized as the average standardized factor score across Waves 1 and 2 (Wave 1 Cronbach’s alpha = .74, Wave 2 = .75; r = .53). Covariates. Objective measures of low social integration were included to account for potential confounding. At Wave I, respondents were given the
LONELINESS AND HEALTH
513
opportunity to list their five closest female and five closest male friends. Three variables were created based on respondents (1) nominating two or fewer friends, which was dichotomously coded as ≤2 Out-Nominations, (2) respondents who received two or fewer friend nominations were dichotomously coded as ≤2 In-Nominations, and (3) respondents who nominated two or fewer friends and received two or fewer friend nominations were dichotomously coded as a Social Isolate. To account for active social networks outside of school, a measure for having ≤2 Out-of-School Nominations were included in the models. Multiple measures of adolescents’ prior health were included in the analysis to account for previous health conditions that could confound the relationship between adolescent loneliness and adult health. Adolescent health was measured as a continuous variable in Wave 1 based on parent or guardian report of their offspring’s health in adolescence. Parents or guardians were asked, “How would you rate your child’s general physical health? Would you say excellent, very good, good, fair, or poor?” Adolescent health was coded so that higher values reflect better health. Because parent health is also an important predictor of offspring health, parent self-rated health is included as a continuous variable where higher scores indicate better health. In addition we include a dichotomous measure of whether the adolescent had health insurance in Wave 1 to account for healthcare access. Two dichotomous measures of adolescent risk behavior were also incorporated, and both measures were averaged across Waves 1 and 2. Binge drinking was measured as drinking four (females) or five (males) drinks in a row at least once over the past 12 months (r = .41; Rodgers et al. 2005). Respondents who smoked at least one cigarette for 15 to 30 of the prior 30 days were categorized as regular smokers (r = .47; Brook et al. 2006). Additional background controls included respondent gender, mean-centered age at Wave 1, racial identification, and immigrant status. Respondents’ race/ethnicity is categorized in our analysis as non-Hispanic White, African American, Hispanic, Asian/Pacific Islander, and other. Immigrant status was operationalized as a dichotomous measure of whether or not the focal adolescent was born in the U.S. Family background characteristics included parent marital status (married, separated or divorced, single/never married, or widowed), parent education (some high school, high school degree, some college or vocational training, college graduate, professional/ advanced training) measured using either the average of the two parents living in the household or the highest level education of the single parent in the household and the natural log of the average income of parents in the household.
514
BRIDGET J. GOOSBY ET AL.
Analytic Strategy Analyses were conducted using logistic regression. All results used stratum and school clustering adjustments; however, population-level weights were not used because the variables used to create the weights were included in our analyses (Winship and Radbill 1994). The model series were identical for each dependent variable with the exception of the analyses for diagnosed depression, which was included as a covariate in the physical health models. The first model assessed the relationship between loneliness at Wave 1 and the health outcome adjusting for gender, background controls, and confounders including race/ethnicity, age, family structure, immigrant status, youth self-rated health, youth smoking and binge drinking, as well as parents’ income, education, and self-rated health (Model 1). Model 2 further adjusted for high depressive symptoms at Wave 2. Next, friend nomination measures, school attachment, parent support, and key interaction terms were introduced (Model 3). In this model, we include a female 9 loneliness interaction to assess gender differences in the impact of loneliness on early adulthood health, along with loneliness 9 parent support and loneliness 9 school attachment interactions to identify whether parent support and school attachment moderate the loneliness/health relationship. Model 3 is the final model reported for diagnosed depression. For the metabolic health conditions and self-rated health, the final model (Model 4) includes diagnosed depression in Wave 3 to further assess the potential link between depression and later health conditions. Results Sample Characteristics Descriptive statistics for all covariates and the dependent variables included in the models are reported in Table 1. Respondents in our sample were primarily white (48%), 54 percent were females, and the average Wave 1 age was 15.6 years. Most came from married households (73%), and the majority of parents had either a high school degree (30%) or some college or vocational training (29%). Twenty-one percent of the sample reported two or fewer friend in-nominations, while 22 percent reported two or fewer friend out-nominations. Approximately 8 percent of respondents reported two or fewer in- and out-nominations (i.e., social isolates). About 18 percent of youth reported high levels of depressive symptoms at Wave 2. Across Waves 1 and 2, approximately 21 percent of the sample reported binge drinking and 12 percent reported smoking regularly. In Wave 3, 10 percent of young adults reported being diagnosed with depression and 4 percent reported having poor/fair selfrated health. Thirty-five percent of young adult respondents were overweight or
Adolescent stressors, risk, and protective mechanisms Loneliness W1e 10,512 High depressive symptoms W2 10,549 School attachment (average W1–W2)e 10,462 Parent support (average W1–W2)e 10,440 Binge drinking (average W1–W2) 10,521 Regular smoking (average W1–W2) 10,549 Covariates
